A universal rule of all things electronic is that later versions are almost always superior to the initial versions.
Electronic health records (EHRs) have not been immune to this rule. Almost a decade ago, a goal was set for this technology to replace and centralize the nation’s mountain of disparate paper medical records by 20141; however, the availability of EHRs in hospitals and clinics has spread considerably slower than anticipated.2,3
The US Department of Health and Human Services has given itself praise for a 41% jump in the use of EHRs since 2008, but benchmarks toward the promised land of point-and-click patient records only serve to remind health care professionals that much remains to be accomplished. Complicating the process even more is the current political debate over a sitting president’s public health care plan and a delayed national EHR system with $30 billion in federal support,4 which has each contributed to waning public enthusiasm for additional health care spending.
This kind of unglamorous publicity of EHRs is unfair to a technology that has become something quite amazing to behold, said Christina Bivona-Tellez, Global Health and Human Services Manager for ESRI, a software company based in Redlands, CA.5 ESRI is one of many rapidly growing technology companies that specializes in using technology to make observations—that are otherwise elusive—from massive, unrelated volumes of data. ESRI clients include both the US Centers for Disease Control and European Centers for Disease Control as well as 80% of the Ministries of Health Worldwide. Health care makes up 10% of its growing business, said Bivona-Tellez.
EHR technology now has the power to weave “tapestry data” about an individual’s residence, local air quality, socioeconomic status, reading and eating habits, and even product brand preference into a patient portrait that can be matched up against traditional medical records to vastly improve diagnostic accuracy and treatment, Bivona-Tellez said. The picture a doctor can get of a patient, their medical history, their occupation and stress level, and other factors is limited only by the data available. Given enough information to work with, ESRI software can, for example, quickly predict the spread of a flu virus from unrelated databases containing information on wind direction, airline passenger information, emergency room admissions, and other scenarios, explained Bivona-Tellez.
“We want to have as much information as possible so we can make informed decisions,” said Bivona-Tellez. “In health care, we are making suppositions about cause and effect. So now we want to know more about risk factors and what we can do to help prevent the emergence, or delay the emergence, of different health conditions.”
Increasingly Worth the Wait
EHR technology introduced by the Veteran’s Administration in 1972 under the name VistA was, in the opinion of some, too primitive for clinicians to adopt. Today’s EHR platforms more closely resemble video games in the way information is sorted and displayed. These types of cutting-edge EHR products were on display in mid-October in Cambridge, MA, at an ESRI conference on Geospatial Treatment.
Geospatial Treatment is the term used to describe how vast amounts of information about a patient’s surroundings and behavior can be mapped in ways that present unique patterns in diagnosis and care. Bivona-Tellez added that she has no qualms with saying that money is very much a part of the problem when it comes to achieving the vision of global EHRs. She offered the example of South Korea, which leads the world in Internet connections per-household because the government requires it and also provides funding.6 In the United States, the availability of EHRs depends on the decisions of the free market, she said.
“There is competition in the market to deliver the most affordable EHR services, and the issue is that it’s expensive to do so,” said Bivona-Tellez.
The federal government, which was responsible for mandating EHRs, has been paying incentives to doctors’ offices and health care provider networks to make investments in the technology.5 Still, the cost of an EHR network to a small medical practice is prohibitive. Large research hospitals still barely have working EHR systems that produce results any better than pulling a patient file by hand, so it’s the genuinely large EHR deployments that are having the most success and getting the most attention, said Bivona-Tellez.
For example, the Indiana Network for Patient Care (INPC) successfully merged its bulging EHR database with a community information system (CIS) managed by its neighbor The Polis Center at Indiana University-Purdue University, in Indianapolis, IN. INPC brought to the table records of 14,000 physicians, statewide syndromic surveillance data, public health care detection records, and a data repository with over 1 billion digital clinical observations dating back more than 30 years. In addition, INPC added data on more than 1 million daily clinical transactions from 200 data sources, including 80 emergency rooms, 35 hospitals, and more than 100 clinics.7
Integrated into INPC’s data from The Polis Center were volumes of data from communities in the 11-county Indianapolis metropolitan area; variables from 1980 to the present included welfare, education, health, public safety, housing, and demographics. The project took over a year to complete at an unreported cost, but INPC and The Polis Center determined that when community, socioeconomic, and environmental data is introduced in EHRs, “these systems also can more effectively identify and characterize public health trends and events, predict future public health outcomes, and help devise more effective health interventions.”7
Cost is hard to pinpoint in an EHR deployment because there are multiple expenses to take into account, including new software and computers as well as billable hours to create and maintain the EHR networks. In 2011, a medical network of 26 primary care practices in Texas deployed an EHR system that cost about $162,000, plus an additional $85,500 for first-year maintenance.8
Is It Really That Complicated?
Even for data systems that are miles apart, as in the example of INPC and The Polis Center, linking the information can be a daunting task. Despite the challenges, a system has been created in Houston, TX, that a properly authorized physician could access from anywhere in the world in order to get extensive and accurate EHRs; this would operate in a similar fashion as purchasing a product online from Amazon.com®.
This data system, housed at the Health Disparities Research Department of the University of Texas M.D. Anderson Cancer Center (MDACC), is managed by Seann Regan, MA, a geographic information systems analyst. Much of the data used by Regan and his colleagues at MDACC, for example, when researching instances of thyroid cancer related to socioeconomic and race and ethnicity factors in Texas between 1995 and 2008,9 comes from easily accessible public data from census, geographic, community, and public works databases (including the National Aeronautics and Space Administration), all at no expense. Additionally, there is plenty of room for more data to throw into the mix, said Regan, who added that he would like to include more ecological data and information related to factors such as pollen and sunlight exposure.
The Health Disparities Research data program that Regan runs at MDACC could easily serve up EHR records for a nationwide network in real time if it simply had more processing power—something easily available today if the money is there to pay for it, said Regan. “This database could certainly be used, and is used, as a real-time EHR database. And it’s scalable enough to provide real-time service,” said Regan.
The question that arises now is: how do we build the EHR computer network? Is it created from a single super computer like the one at MDACC, which serves EHRs nationwide, or from separate networks that fetch EHRs from separate clinics and groups? Shared computer systems are inherently more vulnerable to security breaches. Patient privacy and information security play an increasing role in EHR decision-making, and it may be an issue that never goes away as few see any advantage to having less information about a patient versus more.
“The challenge is how to integrate all the available data ethically and improve care and access with our predictive power without invading people’s privacy,” said Regan.
One of Regan’s coauthors on the thyroid cancer study is Lorraine Reitzel, PhD, an assistant professor in the Department of Health Disparities Research at MDACC, who recently completed a study that examined the surrounding social and environmental factors of patients with head and neck cancer. This study looks closely at relationships between patients and their environments in attempt to discover whether there are simply more cases of head and neck cancer occurring, or if greater access to health care is resulting in higher counts of recorded diagnosis.10
“Maybe we are not at the point where we definitively know, based on empirical science, whether or not some of these environmental variables truly have an effect on cancer incidences, cancer treatment, and survival,” Reitzel said. “But doctors need this patient information, even if it’s not actionable at the present time. We do not yet know how significant it will become.”
Dr. Reitzel is a strong advocate of implementing EHRs to benefit patient care and treatment, but she understands that making sense of massive amounts of patient data is just part of the universal fight against cancer. As Dr. Reitzel explains, access to EHRs and the improvements being made to the technology is not where the responsibility of oncologists stop, but rather, where it begins.
- Hansen D. EMR deadline does not compute: falling short of 2014 goals. American Medical News. May 19, 2008. https://www.clinicaladvisor.com/quiz/derm-dx-pain-at-the-base-of-a-fingernail/. Accessed November 8, 2013.
- Kerner L. EHR adoption rate at tipping point. Healthcare Technology Online. May 29, 2013. http://www.healthcaretechnologyonline.com/doc/ehr-adoption-rate-at-tipping-point-0001. Accessed November 8, 2013.
- MixPanel. IOS7 adoption rate. October 25, 2013. https://mixpanel.com/trends/#report/ios_7/from_date:-10,to_date:0. Accessed November 11, 2013.
- Di-Natale D. Another ObamaCare ‘Glitch’: $30B blown on non-operational medical record system. Foxnews.com. October 15, 2013. http://www.foxnews.com/politics/2013/10/15/another-obamacare-glitch-30b-blown-on-non-operational-medical-record-system/. Accessed October 25, 2013.
- ESRI company website. http://www.esri.com/. Accessed October 25, 2013.
- Wikipedia. Internet in South Korea. http://en.wikipedia.org/wiki/Internet_in_South_Korea. Accessed October 25, 2013.
- Comer KF, Grannis S, Dixon BE, et al. Incorporating Geospatial capacity within clinical data systems to address social determinants of health. Public Health Rep. 2011;126(suppl 3):54-61.
- McBride M. Understanding the true costs of an EHR implementation plan. Medical Economics. July 25, 2012. http://medicaleconomics.modernmedicine.com/medical-economics/news/modernmedicine/modern-medicine-feature-articles/understanding-true-costs-ehr-. Accessed October 25, 2013.
- Reitzel L, Nguyen N, Li N, et al. Trends in thyroid cancer incidence in Texas from 1995 to 2008 by socioeconomic status and race/ethnicity. Thyroid. 2013 Sep 24. [Epub ahead of print]
- Reitzel LR, Nguyen N, Zafereo ME, et al. Neighborhood deprivation and clinical outcomes among head and neck cancer patients. Health Place. 2012;18(4):861-868.
This article originally appeared on Cancer Therapy Advisor